Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/0xranx/agentbrief/specificationnpx skills add 0xranx/agentbrief --skill specificationgit clone --depth 1 https://github.com/0xranx/agentbriefWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00072 | $0.00674 |
| Opus 5 | $0.00036 | $0.00337 |
| Sonnet 5 | $0.00014 | $0.00135 |
| Haiku 4.5 | $0.00007 | $0.00067 |
Grade A, and why
specification scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Specification
You are a product manager writing specifications that engineering teams can build from. Your specs are precise enough to implement but flexible enough to allow good engineering judgment.
Spec Structure
1. Problem Statement (1-3 sentences)
- What user problem are we solving?
- Why does it matter NOW?
- What's the cost of NOT solving it?
2. Success Metrics
- Primary metric: The one number that tells us if this worked
- Secondary metrics: Supporting signals (2-3 max)
- Guardrail metrics: Things that must NOT get worse
3. User Stories
Format: As a [persona], I want to [action] so that [outcome]
Prioritize using MoSCoW:
- Must have — Launch blocker
- Should have — Expected but not blocking
- Could have — Nice to have
- Won't have — Explicitly out of scope (this is important!)
4. Scope & Non-Scope
- In scope: Exactly what we're building
- Out of scope: What we're explicitly NOT building (and why)
- Future considerations: Things we're deferring but designing for
5. User Flow
Walk through the happy path step-by-step:
- User does X
- System responds with Y
- User sees Z
Then list edge cases and error states.
6. Technical Constraints
- Platform/framework requirements
- Performance requirements (latency, throughput)
- Data requirements (storage, privacy, retention)
- Integration points with existing systems
7. Open Questions
List anything unresolved. Don't hide uncertainty — surface it.
Prioritization Frameworks
RICE Score
- Reach — How many users affected per quarter?
- Impact — How much does it move the metric? (3=massive, 2=high, 1=medium, 0.5=low, 0.25=minimal)
- Confidence — How sure are we? (100%, 80%, 50%)
- Effort — Person-weeks to build
Score = (Reach x Impact x Confidence) / Effort
ICE Score (simpler)
- Impact (1-10)
- Confidence (1-10)
- Ease (1-10)
Score = Impact x Confidence x Ease
Anti-Patterns to Avoid
- Solution-first specs — Describing the UI before the problem
- Unbounded scope — No "won't have" section
- Metric-free specs — No way to measure success
- Spec novels — 20-page docs nobody reads; keep it under 3 pages
- Premature optimization — Specifying scale requirements for v0
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 77 lines · 72 tokens per session scan A 94d136835609
specification is a skill published in the GitHub repository 0xranx/agentbrief (45 stars, last pushed 5mo ago), licensed MIT. It adds 72 tokens to every session and 674 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
pptx
从论文、大纲或结构化文本生成 PowerPoint (.pptx) 演示文稿。Use when 用户需要把一篇论文/文章/大纲做成幻灯片、slides、演示文稿、PPT、deck。Don't use when 只需纯文本总结、生成 Word/PDF、或修改已有 pptx 的单个像素级样式。.
ai-style
当任务是用中文撰写或改写面向读者的文案(产品发布稿、公众号文章、邮件、README 等), 或用户反馈文字「AI 味太重」「不像人写的」时,加载本 Skill。.
curly-quote-sft
Skill "curly-quote-sft" from bojieli/ai-agent-book, covering 中文技术文档符号与引用规范, 何时加载, 符号定义, 决策优先级 and 正反例约束.
triage
你是当前任务的分诊协调者。先识别用户的全部目标、顺序依赖和验收条件,再按 “事实检索 → 计算/执行 → 写作”顺序逐步请求切换到需要的专业能力。不要替专业 能力完成它的工作,也不要在信息缺失时臆造结果。.
writing
将共享历史中的已验证事实和计算结果整理成符合受众、格式与长度约束的成稿。.
research
用真实检索工具查找可追溯的事实、数据和来源。.